class_docstr: Graph isomorphism block.
docstr: Initializes a GIN block.
  
  Args:
    mlp_layers: (int) Number of mlp layers in GIN
    hidden_dim: (int) Dimension of hidden layer.
    dropout_rate: (float) Dropout probability
    learn_eps: (bool) Whether to learn the epsilon weighting
    sparse: (bool) Whether features are sparse
    **kwargs: Keyword arguments for tf.keras.layers.Layer.
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code: def __init__(
      self,
      mlp_layers,
      hidden_dim,
      dropout_rate,
      learn_eps,
      sparse,
      **kwargs,
  ):
      """Initializes a GIN block.
  
      Args:
        mlp_layers: (int) Number of mlp layers in GIN
        hidden_dim: (int) Dimension of hidden layer.
        dropout_rate: (float) Dropout probability
        learn_eps: (bool) Whether to learn the epsilon weighting
        sparse: (bool) Whether features are sparse
        **kwargs: Keyword arguments for tf.keras.layers.Layer.
      """
      super(GINBlock, self).__init__(**kwargs)
      self.mlp_layers = mlp_layers
      self.hidden_dim = hidden_dim
      self.dropout_rate = dropout_rate
      self.learn_eps = learn_eps
      self.sparse = sparse
  
      self._activation = tf.keras.layers.ReLU()
      self._dropout = tf.keras.layers.Dropout(self.dropout_rate)
  
      self._graph_iso_layer = GraphIsomorphismLayer(
          self.mlp_layers,
          self.hidden_dim,
          self.dropout_rate,
          learn_eps=self.learn_eps,
          sparse=self.sparse,
      )
  
imports: from layers import GraphAttnLayer
  from layers import GraphConvLayer
  from layers import GraphIsomorphismLayer
  from layers import SparseGraphAttnLayer
  import tensorflow
label_desc: Use image node_id 1 to create a new GINBlock object from inherited base classes: tf.keras.layers with example: obj = GINBlock(mlp_layers, hidden_dim, dropout_rate, learn_eps, sparse)